Family-Level Multimorbidity among Older Adults in India: Looking through a Syndemic Lens

Abstract

Most evidence on multimorbidity is drawn from an individual level assessment despite the fact that multimorbidity is modulated by shared risk factors prevailing within the household environment. Our study reports the magnitude of family-level multimorbidity, its correlates, and healthcare expenditure among older adults using data from the Longitudinal Ageing Study in India (LASI), wave-1. LASI is a nationwide survey amongst older adults aged ≥45 years conducted in 2017–2018. We included (n = 22,526) families defined as two or more members coresiding in the same household. We propose a new term, “family-level multimorbidity”, defined as two or more members of a family having multimorbidity. Multivariable logistic regression was used to assess correlates, expressed as adjusted odds ratios with a 95% confidence interval. Family-level multimorbidity was prevalent among 44.46% families, whereas 41.8% had conjugal multimorbidity. Amongst siblings, 42.86% reported multimorbidity and intergenerational (three generations) was 46.07%. Family-level multimorbidity was predominantly associated with the urban and affluent class. Healthcare expenditure increased with more multimorbid individuals in a family. Our findings depict family-centred interventions that may be considered to mitigate multimorbidity. Future studies should explore family-level multimorbidity to help inform programs and policies in strategising preventive as well as curative services with the family as a unit.

Epidemiology and impact of chronic disease multimorbidity in India: a systematic review and meta-analysis

“…Sensitization of frontline workers such as Accredited Social Health Activist (ASHA) and Community Health Officer (CHO) towards the needs of multimorbid individuals is required with a focus on family-level interventions for shared risk factors. 77 Capacity building of primary care staff to manage multimorbidity is also needed. Nonetheless, most LMICs face a similar healthcare challenge in combating multimorbidity where the determinants, patient outcomes as well as impact of multimorbidity on health system remain alike.…”

Characterizing Multimorbidity Prevalence and Adverse Outcomes in Ethnically and Culturally Diverse Sub-Populations in India: Gaps, Opportunities, and Future Directions

“…Our narrative review was based on 15 articles. To address Objective 1, we summarized the findings from eight articles on the definition, measurement, prevalence, and burden of multimorbidity across sub-populations, presented in Table 1 [ 9 , 10 , 14 , 18 , 19 , 21 , 22 , 23 ] and Table 2 [ 12 , 18 , 24 , 25 , 26 , 27 , 28 , 29 ]. Additionally, in Table 2 , we summarize the findings of the remaining seven articles that reported the associations between multimorbidity and specific adverse health outcomes to address Objective 2.…”

“…Our narrative review was based on 15 articles. To address Objective 1, we summarized the findings from eight articles on the definition, measurement, prevalence, and burden of multimorbidity across sub-populations, presented in Table 1 [9,10,14,18,19,[21][22][23] and Table 2 [12,18,[24][25][26][27][28][29]. Additionally, in Table 2, we summarize the findings of the remaining seven articles that reported the associations between multimorbidity and specific adverse health outcomes to address Objective 2. verbal fluency score, 16 which was the number of named animals within 60 s; the community screening instrument for dementia score 17; and the Raven test, 18 a count of the number of correct answers to a series of images that required the respondent to select the missing piece.…”

“…We identified health disparity populations who are at risk of multimorbidity and described the prevalence and types of adverse outcomes associated with multimorbidity based on 15 key and emerging papers. While previous research has examined multimorbidity in individual studies utilizing LASI data [ 9 , 10 , 12 , 14 , 15 , 16 , 17 , 18 , 19 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 ], our narrative review is a focused synthesis of the current state of multimorbidity in India. Our review highlights specific populations that are vulnerable, with a higher multimorbidity prevalence that can be targeted for intervention and policy to ameliorate the consequences of multimorbidity in India.…”

Prevalence and correlates of multimorbidity among patients attending AYUSH primary care settings in Delhi-National Capital Region, India

“…Nonetheless, down referral and up referral to secondary or tertiary levels of care are still important. Family-level approaches to the management of multimorbidity, which include the prevention of shared risk factors, are warranted [ 36 ]. Behavioral change communication for prevention is the most important step that AYUSH primary care practitioners should incorporate into their daily clinical practice.…”